DocumentCode
2069176
Title
Efficient Recommender Systems
Author
Bergemann, D. ; Ozmen, Deran
Author_Institution
Yale Univ., New Haven, CT
fYear
2006
fDate
26-29 June 2006
Firstpage
41
Lastpage
41
Abstract
We study the efficient allocation of buyers in the presence of recommender systems. A recommender system affects the market in two ways: (i) it creates value by reducing product uncertainty for the customers and hence (ii) its recommendations can be offered as add-ons, which generates informational externalities. We investigate the impact of these factors on the efficient allocation of buyers across different products. We find that the efficient allocation requires that the seller with the recommender system has full market share. If the recommender system is sufficiently effective in reducing uncertainty, it is optimal to have some products to be purchased by a larger group of people than others. The large group consists of customers with flexible tastes
Keywords
information filters; resource allocation; retail data processing; buyer allocation; product uncertainty; recommender systems; Recommender systems;
fLanguage
English
Publisher
ieee
Conference_Titel
E-Commerce Technology, 2006. The 8th IEEE International Conference on and Enterprise Computing, E-Commerce, and E-Services, The 3rd IEEE International Conference on
Conference_Location
San Francisco, CA
Print_ISBN
0-7695-2511-3
Type
conf
DOI
10.1109/CEC-EEE.2006.42
Filename
1640296
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